Temporal parameters calculation

This example illustrates how temporal parameters can be calculated for each stride by the TemporalParameterCalculation.

Getting stride list

For this we need stride event list that can be obtained from event detection method.

from gaitmap.example_data import get_healthy_example_stride_events
from gaitmap.parameters import TemporalParameterCalculation

stride_list = get_healthy_example_stride_events()

Creating TemporalParameterCalculation object

We need this object for calculating the temporal parameters. Temporal parameters are calculated based on ic and tc events

p = TemporalParameterCalculation()
p = p.calculate(stride_event_list=stride_list, sampling_rate_hz=204.8)

Inspecting the results

The main output is the parameters_, which contains the temporal parameters for each stride in format of data frame in case of single sensor or dictionary of data frames for multiple sensors. As our passed stride_list here consists of two sensors, the output will be a dictionary.

p.parameters_["left_sensor"]

	stride_time	swing_time	stance_time
s_id
0	1.069336	0.346680	0.722656
1	1.074219	0.361328	0.712891
2	1.069336	0.351562	0.717773
3	1.069336	0.351562	0.717773
4	1.049805	0.351562	0.698242
5	1.049805	0.351562	0.698242
6	1.049805	0.351562	0.698242
7	1.069336	0.361328	0.708008
8	1.079102	0.346680	0.732422
9	1.079102	0.356445	0.722656
10	1.103516	0.351562	0.751953
11	1.098633	0.361328	0.737305
12	1.152344	0.371094	0.781250
13	2.275391	1.499023	0.776367
14	1.162109	0.380859	0.781250
15	1.098633	0.356445	0.742188
16	1.069336	0.356445	0.712891
17	1.083984	0.361328	0.722656
18	1.059570	0.351562	0.708008
19	1.079102	0.351562	0.727539
20	1.088867	0.351562	0.737305
21	1.088867	0.346680	0.742188
22	1.103516	0.361328	0.742188
23	1.108398	0.380859	0.727539
24	1.108398	0.356445	0.751953
25	1.123047	0.371094	0.751953
26	1.127930	0.361328	0.766602
27	1.132812	0.371094	0.761719

parameters_pretty_ is another version of parameters_ but using human readable column names that indicate units.

p.parameters_pretty_["left_sensor"]

	stride time [s]	swing time [s]	stance time [s]
stride id
0	1.069336	0.346680	0.722656
1	1.074219	0.361328	0.712891
2	1.069336	0.351562	0.717773
3	1.069336	0.351562	0.717773
4	1.049805	0.351562	0.698242
5	1.049805	0.351562	0.698242
6	1.049805	0.351562	0.698242
7	1.069336	0.361328	0.708008
8	1.079102	0.346680	0.732422
9	1.079102	0.356445	0.722656
10	1.103516	0.351562	0.751953
11	1.098633	0.361328	0.737305
12	1.152344	0.371094	0.781250
13	2.275391	1.499023	0.776367
14	1.162109	0.380859	0.781250
15	1.098633	0.356445	0.742188
16	1.069336	0.356445	0.712891
17	1.083984	0.361328	0.722656
18	1.059570	0.351562	0.708008
19	1.079102	0.351562	0.727539
20	1.088867	0.351562	0.737305
21	1.088867	0.346680	0.742188
22	1.103516	0.361328	0.742188
23	1.108398	0.380859	0.727539
24	1.108398	0.356445	0.751953
25	1.123047	0.371094	0.751953
26	1.127930	0.361328	0.766602
27	1.132812	0.371094	0.761719

Estimated memory usage: 9 MB